Comprehensive side-by-side LLM comparison
Gemma 3 12B leads with 36.0% higher average benchmark score. Gemma 3 12B offers 221.2K more tokens in context window than Gemini 1.0 Pro. Gemma 3 12B is $1.85 cheaper per million tokens. Gemma 3 12B supports multimodal inputs. Overall, Gemma 3 12B is the stronger choice for coding tasks.
Gemini 1.0 Pro is a language model developed by Google. The model shows competitive results across 9 benchmarks. Notable strengths include BIG-Bench (75.0%), MMLU (71.8%), WMT23 (71.7%). The model is available through 1 API provider. Released in 2024, it represents Google's latest advancement in AI technology.
Gemma 3 12B is a multimodal language model developed by Google. It achieves strong performance with an average score of 62.5% across 26 benchmarks. It excels particularly in GSM8k (94.4%), IFEval (88.9%), DocVQA (87.1%). It supports a 262K token context window for handling large documents. The model is available through 1 API provider. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents Google's latest advancement in AI technology.
1 year newer
Gemini 1.0 Pro
2024-02-15
Gemma 3 12B
2025-03-12
Cost per million tokens (USD)
Gemini 1.0 Pro
Gemma 3 12B
Context window and performance specifications
Average performance across 33 common benchmarks
Gemini 1.0 Pro
Gemma 3 12B
Gemini 1.0 Pro
2024-02-01
Available providers and their performance metrics
Gemini 1.0 Pro
Gemma 3 12B
Gemini 1.0 Pro
Gemma 3 12B
Gemini 1.0 Pro
Gemma 3 12B
DeepInfra